Method of automatically determining flaws of an object of examination

ABSTRACT

In a method of automatically determining flaws of an object of examination according to the invention, rays of light are transmitted through on object of examination, while adjusting the depth of observation to make it agree with the focal length of a detected flaw, go down deeper than the focal length and come up shallower than the focal length and the brightness of transmitted light for each depth of observation is converted into a corresponding electric signal. Portions of the generated signal that are found outside a predetermined range of intensity are taken out as flaw signals and the obtained flaw signals are compared with a number of binarized flaw patterns prepared from various flaws that have been detected in advance to accurately determine the type, number and size of the detected flaws.

BACKGROUND OF THE INVENTION

1. Field of the Invention

This invention relates to a method of detecting flaws of an object ofexamination by using optical and electric (electronic) means andautomatically determining the type and nature of each of the detectedflaws.

2. Prior Art

Flaws on and/or in a product can seriously damage the performance of theproduct and significantly reduce its commercial value.

For instance, foreign objects contained in the insulation layers ofrubber or plastic of a cable can significantly degrade the insulationbreakdown characteristics of the cable.

While the probability with which foreign objects are introduced intoinsulation layers of rubber or plastic insulated cables has been greatlyreduced with the recent development in the field of manufacture ofinsulated cables, there will still be a long way to go before flawlesscables are produced.

Therefore, it is of vital importance to accurately analyze theinsulation breakdown characteristics of each cable by examining thetype, the size and the number of the flaws of the cable if it ismarketed with a reliable degree of quality assurance.

In the case of an extra high voltage power cable, a minute foreignobject that can be detected only by microscopic scrutiny using amicroscope of a high magnification can seriously affect the insulationbreakdown characteristics of the power cable if it is contained in anyof its insulation layers. Therefore, a highly reliable inspection systemshould be established to cope with such problems, involving a largenumber of specimens to be examined, in order to provide an enhancedlevel of quality assurance for cables of this category.

The most dangerous foreign object is, of course metal debris. In orderto safely eliminate metal debris from marketed cables, the type andnature of foreign objects should be determined before knowing the sizeand the number of the foreign objects for each type.

It is a common practice for examining the quality of a rubber or plasticinsulation layer of an insulated cable to cut out a specimen having athickness of 0.05 to 2 mm from the layer and observe the specimenthrough a microscope to visually determine the type, the number and thesize of the flaws found in it.

Observation of a specimen proceeds in this technique proceeds in threestages: detecting flaws in the specimen, identifying each of thedetected flaws by color and shape and metering the dimensions of each ofthe flaws (length×width×height).

Flaws in rubber or plastic insulated cables may normally grouped intothree categories: ambers, black foreign objects and voids. Metal debrisare regarded as black foreign objects.

When flaws are observed through a microscope that receives rays of lighttransmitted through the object of examination, each may take any of thefollowing image patterns depending on the depth of observation along thecenter line of the microscope running through the focal point of thelens system.

Just: signifying that the depth of observation agrees with the focallength of the flaw. Under: indicating that the depth of observation isshallower than the focal length of the flaw. Over: meaning that thedepth of observation is deeper than the focal length of the flaw.

These image patterns are summarized in Table 1.

Black foreign objects clearly appear black when the depth of observationis just and blurred and black when the depth of observation is under orover.

Ambers are hardly or not recognizable when the depth of observation isjust because they turn totally white and do not make difference with theambient resin color. They take on a black margin surrounding a whiteinside area when the depth of observation is over, whereas they areobserved as totally black when the depth of observation is under.

Voids shows a black margin with the inside appearing white when thedepth of observation is just, although they look just black when thedepth of observation is under or over.

The effect of the above described technique of determining flaws byobservation greatly depends on the skill of the operator working at themicroscope and hence subject to deviations in terms of the accuracy ofobservation. Moreover, it is a time and labor consuming technique.

In an attempt to bypass this problem, there have been utilized automaticflaw detecting apparatus that are popularly used in other technologicalfields for detecting flaws of cable insulation layers.

With an apparatus of this type, flaws in a specimen of a cableinsulation layer having an appropriate thickness can be automaticallydetected by differences in the level of brightness of the lighttransmitted through the specimen.

Referring to graphs (a) and (b) of FIG. 22 of the accompanying drawings,the apparatus may automatically recognize areas having a brightnesslower than a predetermined threshold level X as flaws. Conversely, areashaving a brightness higher than the threshold level X may be recognizedas so many flaws by the apparatus.

This technique of automatic flaw detection is, however, also not withoutproblems.

Firstly, when flaws are automatically identified by referring to thebrightness of transmitted rays of light that can be higher or lower thana threshold level X, both voids that are over or under and ambers thatare under appear black to the automatic flaw detector and it fails todiscriminate them from each other and from black foreign objects.

Then, the net result will be incapability of meeting the requirement ofclassification of flaws before counting of the number and measuring thesize of the flaws as in the case of microscopic observation by men.

Secondly, not only black foreign objects in the vicinity of the surfaceof the specimen but also scars on the surface (that can give rise tonoise) can be recognized as black by the automatic detector if thethreshold level X is held too high or low to enhance the sensitivity ofthe detector. Then, the detector will become totally powerless for flawdetection.

Thirdly, when the specimen has an uneven thickness, thin areas (brightareas) of the specimen can be recognized as white by the automaticdetector.

Such white areas may be hardly discriminated from ambers which also lookwhite when the depth of observation agrees with the focal length of theflaws.

As far as rubber or plastic insulated power cables are concerned, anirregular interface between a semi-conductive layer and an insulationlayer can also provide causes of false recognition.

Some of the technological problems related to irregular interfaces andthe currently available methods for determining irregularities oninterfaces will be described below.

Referring to FIG. 15 of the accompanying drawings, which illustrates incross-section a rubber or plastic insulated power cable having an innersemi-conductive layer 11, an insulation layer 14 and an outersemi-conductive layer 12, a tree (ramified crack) can develop in theinsulation layer 14 if there is an irregular area in the interface 15 ofthe inner and/or outer semi-conductive layer 12 and the insulation layer14 as the electric field generated in and around the cable shows a highdegree of concentration there.

A flaw of this type can also lead to a degraded performance of the cableand eventually break down the insulation layer 14.

In view of the current circumstances for power cables, where rubber orplastic insulated cables and particularly bridged polyethylene insulatedcables are used for extra high voltage applications involving voltagesas high as 2,75 KV, cables of this type need to be carefully andmicroscopically scrutinized by using a large number of specimens pereach cable so that any irregularities on interfaces of layers may berigorously checked.

A known practice of microscopically examining specimens to meet rigorousrequirements for high voltage applications of sheathed cables is takingspecimens (such as an object of examination 17 in FIG. 16) having athickness of approximately 0.5 mm out of a cable by means of a microtomeand then visually scrutinizing them through a microscope.

Assume here that a specimen as shown in FIG. 16 is prepared by means ofa microtome. Of the specimen 17 of FIG. 16, only a limited small area 18may be observed by a single operation of microscopic examination toproduce an image, for instance, as shown in FIG. 17(A).

In FIG. 17(A), the shadowed area 11 or 12 is an opaque inner or outersemi-conductive layer of the object of examination 17 and the white area14 indicates a transmissive insulation layer, the interface 15 of thetwo layers being also shown as a shadowed area.

The inner or outer semi-conductive layer 11 or 12 is tapered along theinterface 15 as seen from FIG. 17(C), which is a sectional view along Y₁--Y₁ line of FIG. 17(A).

An irregularity 16 found on the interface 15 is in fact part of theinner or outer semi-conductive layer 11 or 12 semispherically projectingtoward the insulation layer 14 as shown in FIG. 17(C), which is asectional view along Y₂ --Y₂ line of FIG. 17(A).

Then the detected irregularity 16 may be measured for its width W,height H and surface area as illustrated in FIG. 17(A). The number ofirregularities in the specimen 17 may also be counted.

The above described procedure of detecting and identifying flaws(interface irregularities) is time consuming particularly when a largenumber of specimens are involved because the width and height of eachflaw can be very small and normally found to be around several μm.

Moreover, the reliability such a flaw checking technique may bequestioned because it relies heavily on the human vision while minuteirregularities of the order of micromillimeters need to be controlled tomeet the current technological requirements.

There has been proposed a technique that utilizes the phenomenon thatirregularities normally take the form of a semisphere as shown in FIG.17(C) and present a shady graduation when they are magnified. In adetector realized by using this technique, a threshold value is set fordetecting dark areas of irregularities and an electric signal isgenerated each time it detects an irregular spot.

While this technique may provide some help for flaw detection, it is notcapable of identifying the boundary line of an irregular spot existingon the interface of a semi-conductive layer and an insulation layerbecause it can only detect the darkest areas of irregularities thatexceed a preset threshold level of darkness.

In short, there have not been practically feasible methods and apparatuscapable of automatically detecting irregularities on various interfaces.

SUMMARY OF THE INVENTION

It is therefore a first object of the present invention to provide amethod of accurately detecting flaws in an object of examination andautomatically determining the type, the number and the size of thedetected flaws.

A second object of the present invention is to provide a method ofautomatically determining flaws which is capable of automaticallydetecting flaws on the interface of a semi-conductive layer and aninsulation layer of a cable under examination and generating electricsignals representing them.

According to an aspect of the present invention, the first object of theinvention is achieved by providing a method of automatically determiningflaws of an object of examination by transmitting rays of light throughthe object to detect flaws on and in the object on a one by one basiscomprising a step of adjusting the depth of observation in three stagesof making it agree with the focal length of a detected flaw, go downdeeper than the focal length and come up shallower than the focal lengthand converting the brightness of transmitted of light into acorresponding electric signal for each stage by photoelectric conversionmeans, a step of selecting portions of the generated signal that arefound outside a predetermined range of intensity as flaw signals and astep of comparing each of the flaw signals with a number of binarizedflaw patterns prepared from various flaws that have been detected inadvance.

According to another aspect of the invention, the second object of theinvention is achieved by providing a method of automatically determiningflaws of an object of examination taken out of an inner or outersemi-conductive layer and an adjoining insulation layer of a cable bytransmitting rays of light through the object to detect flaws in theobject comprising a step of converting the brightness of the lighttransmitted through the interface of the semi-conductive layer and theinsulation layer of said object of examination into a correspondingelectric signal by photoelectric conversion means and converting theobtained electric signal further into a corresponding differentiatedelectric signal and a step of selecting portions of the generated signalthat are found outside a predetermined range of intensity asirregularity signals.

A method of automatically determining flaws of an object of examinationaccording to the invention may find various modes of implementation asdescribed below.

In a preferred mode of implementation of the invention, the object ofexamination is divided into a number of virtual layers along its heightand each of the layers is examined for flaws.

In another preferred mode of implementation of the invention, each timea flaw is detected in the object of examination, it is examined todetermine it type and nature by varying the depth of observationrelative to it.

In still another preferred mode of implementation of the invention, theobject of examination is scanned for detection of flaws and, aftercompletion of the scanning operation, each of the detected flaws isscrutinized by varying the depth of observation along a line directed tothe focal point of the flaw.

In still another preferred mode of implementation of the invention, theinsulation layer of the object of examination is heated to a temperaturehigher than the melting point of crystal of the material constitutingthe insulation layer to improve its transparency and rays of light aretransmitted through the interface of said insulation layer and anadjacent semi-conductive layer while the insulation layer is heldtransparent.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a schematic illustration of a preferred embodiment of themethod of automatically determining flaws of an object of examinationaccording to the invention.

FIG. 2 is a schematic illustration of another preferred embodiment ofthe method of automatically determining flaws of an object ofexamination according to the invention.

FIG. 3 is a schematic sectional view of a rubber or plastic insulatedcable that can be examined for flaws by a method according to theinvention.

FIG. 4 is a schematic perspective view of a specimen taken from thecable of FIG. 3.

FIG. 5 is a schematic plan view of the specimen of FIG. 4.

FIG. 6 is a schematic perspective partial view of a specimen shown withvirtual layers.

FIGS. 7a-7i are schematic illustrations showing three different imagesof a specimen produced on the viewing screen of a microscope, graphsshowing the brightness of transmitted light for the respective imagesand the flaw signals obtained from the respective graphs of thebrightness of transmitted of light.

FIGS. 8a-8o are schematic illustrations showing a number of modifiedimages of the flaw of (a) in FIG. 7 projected on a viewing screen of amicroscope by varying the depth of observation, graphs showing thebrightness of transmitted light for the respective images and the flawsignals obtained from the respective graphs of the brightness oftransmitted light.

FIGS. 9a-9o are schematic illustrations similar to FIG. 8 but showing anumber of modified images of the flaws of (b) of FIG. 7 projected on theviewing screen of a microscope by varying the depth of observation,graphs showing the brightness of transmitted light for the respectiveimages and the flaw signals obtained from the respective graphs of thebrightness of transmitted light.

FIGS. 10a-10o are schematic illustrations similar to FIG. 8 but showingmodified images of the flaw of (c) of FIG. 7 projected on the viewingscreen of a microscope by varying the depth of observation, graphsshowing the brightness of transmitted light for the respective imagesand the flaw signals obtained from the respective graphs of thebrightness of transmitted light.

FIGS. 11a-11f are schematic illustrations similar to FIG. 7 but showingtwo different images of a specimen produced on the viewing screen of amicroscope, graphs showing the brightness of transmitted light for therespective images and the flaw signals obtained from the respectivegraphs of the brightness of transmitted light.

FIG. 12 is a schematic illustration showing an image of a specimenproduced on the viewing screen of a microscope.

FIG. 13 is a schematic illustration of another preferred embodiment ofthe method of automatically determining flaws of an object ofexamination according to the invention specifically designed to detectirregularities on an interface of sheath layers of a cable.

FIGS. 14a-14c are schematic illustrations showing, as possiblealternatives, an electric signal, a differentiated electric signal and abinarized signals which are different from those of FIG. 13.

FIG. 15 is a schematic sectional view similar to FIG. 3 but showinganother rubber or plastic insulated cable that can be examined for flawsby a method according to the invention.

FIG. 16 is a schematic perspective view of a part of the cable of FIG.15.

FIG. 17A is a plan view of a specimen taken from the part of FIG. 16 andproduced on the screen of a microscope.

FIGS. 17B and 17C are sectional views of the specimen of FIG. 17A cutrespectively along Y₁ --Y₁ and Y₂ --Y₂ lines.

FIG. 18 is a schematic plan view of a specimen illustrating whereportions of electric signals are taken out.

FIGS. 19a-19z and 19aa are graphic illustrations showing the electricsignals of FIG. 18 and corresponding differentiated electric signals andbinarized signals representing detected flaws.

FIG. 20 is a graphic illustration showing the positional correspondenceof the binarized signals of FIG. 19.

FIG. 21 is a graphic illustration of an arrangement of binarized signalssimilar to FIG. 20 but showing a condition where a higher level ofresolution is realized.

FIGS. 22a and 22b are graphs showing a typical pattern of distributionof brightness of transmitted light in a known flaw detection apparatusand images produced from the fluctuated brightness by a conventionalmethod of automatically determining flaws of an object of examination,respectively.

PREFERRED MODES OF CARRYING OUT THE INVENTION

Now, the present invention will be described in greater detail by way ofpreferred embodiments of the invention.

Referring to FIG. 1 showing a first preferred embodiment of theinvention, rays of light are shed through a specimen 1 as shown in FIG.4 to observe a flaw P of the specimen 1 by means of transmitted light ina microscope.

During the observation, the positional relationship between the specimen1 and the photoelectric converter (e.g., CCD camera) 3 are modified byvarying the depth of observation relative to the focal point of the flawP to produce three different conditions where the depth of observationagrees with the focal point of the flaw P, the former comes up to aposition shallower than the latter and the former goes down deeper thanthe latter.

The brightness of transmitted light under each of these tree conditionsis converted into an electric signal for by a photoelectric converter 3arranged at a position where an optical lens 2 forms a magnified imageof the flaw.

The obtained electric signal having portions a and b that are foundoutside a predetermined range Y of intensity is further converted into abinarized signal comprising corresponding portions c and d representingthe flaws of the specimenm which are then taken out as so many flawsignals for further use.

The pattern of each of the taken out flaw signals c and d (black orwhite) is compared with a number of binarized flaw patterns preparedfrom various flaws that have been detected in advance such as thoseshowin in Table 1 to determine the type of the flaw.

The term "binarize a signal" in the context of this paper means to takeout only portions of signals necessary for image processing of producinga visual image on the screen of a microscope and discarding theremaining unnecessary portions.

The range Y of intensity of electric signal in FIG. 1 is so set that itallows flaws of a specimen 1 to be clearly discriminated from theremaining flawless area, which will be described below.

The lower limit or threshold Y_(L) of the range Y of intensity ofelectric signal is set to a level with which foreign black objects in aspecimen 1 that appear black when processed for a visual image can bediscrimated from dark areas of the specimen. Likewise, the upper limitor threshold Y_(H) of the range Y is set to a level with which ambersthat appear white when processed for a visual image can be discriminatedfrom light areas of the specimen 1 (when the depth of observation agreeswith the focal length of each of them) and voids can also be discerniblefrom light areas of the specimen 1 (when the depth of observation agreeswith the focal length of each of them).

Thus, portions of an electric signal that are found outside the range Ydefined by the two thresholds Y_(L) and Y_(H) are determined to be somany flaws in the spcimen 1.

Black foreign objects, ambers and voids can be clearly identified bycomparing patterns of flaw signals with binarized flaw patterns preparedfrom various flaws that have been detected in advance.

The total area of a specimen 1 to be observed by the embodiment of FIG.1 can be increased to improve the accuracy of flaw detection when thespecimen 1 is realized in the form of a laminate comprising a number oflayers having a thickness of 5, which are examined on a one by one basisto detect flaws P in each layer.

With the embodiment of FIG. 1, each detected flaw P of a specimen 1 canbe scrutinized by modifying the depth of observation for it to determinethe type and nature of the flaw P.

Alternatively, it is possible with the embodiment of FIG. 1 totemprarily store data for the position of each detected flaw P of aspecimen 1 and, after completion of the process of detecting flaws ofthe object, each of the flaws is checked for its type and nature byretrieving the data and observing it anew by modifying the depth ofobservation relative to the focal length.

Referring now to FIG. 2 schematically showing a second preferredembodiment of the invention, the electric signal obtained by way of aphotoelectric converter 3 (e.g., CCD camera) for a specimen 1 is furtherconverted into a differentiated electric signal by a differentiationcircuit 4 and then portions e and f of the differentiated electricsignal which are found out of a predetermined threshold value X ofintensity of differentiated electric signal are taken out as so manyflaw signagnals g and h.

The threshold value X of intensity of differentiated electric signal isso selected that flaws of a specimen 1 can be detected and identified bythe difference bewteen the brightness of the picture elements of thedifferentiated electric signal for the specimen 1 that represent theflaws and that of the picture elements representing the areassurrounding the flaws and or the areas having only superficial scarsand/or an uneven thickness.

Therefore, the second embodiment of the invention can provide a reliablemethod of detecting flaws in a specimen as portions of a differentiatedelectric signal for the specimen 1 found out of a threshold value Xdistinctly represent the flaws in the specimen 1.

Some of the results of exemplary experiments conducted by means of thefirst or second embodiments will be described.

EXAMPLE 1

A 66 KV bridged polyolefine insulated cable having a core conductor 8 ofcopper as well as an outer semi-conductive layer 5, an insulation layerand an inner semi-conductive layer 7 which were respectively 1 mm, 9 mmand 2 mm thick as shown in FIG. 3 was used.

A specimen (object of examination) which was 5 mm long, 5 mm width and0.5 mm thick as shown in FIG. 4 was prepared from the insulation layer 6of the cable and subjected to a process of automatic examination usingthe first embodiment of the invention and a microscope.

The specimen 1 was devided into a number of sections, each having anarea of approximately 500 μm that can be covered by one microscopicobservation as illustrated in FIG. 5.

The sections were sequentially observed through a microscope for flawdetection.

FIG. 7 shows three different images (a), (b), and (c) obtained bymicroscopic observations, each revealing one or more than one flaws inthe specimen.

In FIG. 7, a₁ is a flaw found in the image of (a), b₁ and b₂ are flawsdetected in the image of (b) and c₁ indicates a flow observed in theimage of (c).

Signals (1), (2) and (3) shown respectively in (d), (e) and (f) of FIG.7 represent the respective levels of brightness of transmitted lightpassing through the dotted chain lines.

Only portions of the signals of (d), (e) and (f) in FIG. 7 that fall inzones W (white) or B (black) were recognized by the embodiment and takenout as flaw signals as they were found outside the upper and lowerthresholds.

Consequently, the images of the binarized flaw signals obtained from theabove process showed only black and white spots (B and W) as illustratedin (g), (h) and (i) of FIG. 7.

When the depth of observation for the image (a) of FIG. 7 was variedfrom shallow to deep along a line directed to the focal point of theflaw, the image was modified to appear as (a) through (e) of FIG. 8.

In FIG. 8,(a) and (b) indicate the images obtained when the depth ofobservation was shallow, (c) indicates the image when the depth ofobservation agreed with the focal length of the flaw and (d) and (e)show the images obtained when the depth of observation was deep.

Line graphs (f) through (j) of FIG. 8 respectively show lines (l) ofelectric signals representing the brightness of transmitted lightpassing through the dotted chain lines of (a) through (e).

Of the lines of (f) through (j) of FIG. 8, only portions found in zone B(black) were electrically taken out as indicants of foreign objects andreproduced in images (k) through (o) (more specifically images (l)through (n)) as black spots, which are also listed in row a₁ of Table 2.

Since a₁ was always recognized as B (black) as shown in columns l, m andn in Table 2, the flaw a₁ of FIG. 7(a) was determined to be a blackforeign object when compared with the image patterns of Table 1.

When the depth of observation for the image (b) of FIG. 7 was variedfrom shallow to deep along a line directed to the focal point of theflaws, the image was modified to appear as (a) through (e) of FIG. 9.

In FIG. 9, (a) and (b) indicate the images obtained when the depth ofobservation was shallow, (c) indicates the image when the depth ofobservation agreed with the focal length of the flaw and (d) and (e)show the images obtained when the depth of observation was deep.

Line graphs (f) through (j) of FIG. 9 respectively show lines (2) ofelectric signals representing the brightness of transmitted lightpassing through the dotted chain lines of (a) through (e).

Of the lines of (f) through (j) of FIG. 9, only portions found in zonesW (white) and B (black) were electrically taken out as indicants offoreign objects and reproduced in images (k) through (o) (morespecifically images (l) through (o)) white or black spots, which arealso listed in rows b₁ and b₂ of Table 2.

Flaw b₁ was recognized in three different ways, as B as shown in columnsl and m, as W and B (black margin and white inside) as shown in column nand as W as shown in column o of Table 2, while b₂ was recognized as Bas shown in column l, as W and B as shown in column m and again as W asshown in column 2 of Table 2.

When compared with the image patterns of Table 1, both of the flaws b₁and b₂ of FIG. 7(b) were determined to be ambers.

When the depth of observation for the image (c) of FIG. 7 was variedfrom shallow to deep along a line directed to the focal point of theflaw, the image was modified to appear as (a) through (e) of FIG. 10.

In FIG. 10, (a) and (b) indicate the images obtained when the depth ofobservation was shallow, (c) indicates the image when the depth ofobservation agreed with the focal length of the flaw and (d) and (e)show the images obtained when the depth of observation was deep.

Line graphs (f) through (j) of FIG. 10 respectively show lines (3) ofelectric signals representing the brightness of transmitted lightpassing through the dotted chain lines of (a) through (e).

Of the lines of (f) through (j) of FIG. 10, only portions found in zonesW (white) and 2 (black) were electrically taken out as indicants offoreign objects and reproduced in images (k) through (o) (morespecifically images (l) through (o)) as white and black spots, which arealso listed in row c₁ of Table 2.

Since c₁ was recognized in three different ways, as B as shown incolumns 1 and m, as both W and B as shown in column n and as B as shownin column o of Table 2, the flaw c₁ of FIG. 7(c) was determined to be avoid when compared with the image patterns of Table 1.

Table 3 shows the final result of an operation of determining flawsconducted on the same specimen by an operator (Comparative Example 1)and that of an automatic flaw detection obtained by using a knownautomatic method (Comparative Example 2) as well as that of the aboveexample listed for the purpose of comparison.

As seen from Table 3, the above example (Example 1) produced a finalresult of examination which is as accurate as that of ComparativeExample 1, whereas the result of Comparative Example 2 was by far lessaccurate and totally different from those of both Example 1 andComparative Example 1.

Therefore, it may be safely said that a method of automaticallydetermining flaws of an object of examination according to the inventionis as highly reliable as a visual method involving an operator and canproduce results of examination with a remarkably high level of accuracywhich any conventional methods can never achieve.

The size and number of flaws will be determined by this method for eachcategory in a manner similar to that of a conventional method.

While a specimen was divided into a number of sections, which weresequentially observed through a microscope for detection of flaws inExample 1 as shown in (a) through (c) of FIG. 7, it may be alternativelydivided into virtual layers as shown in FIG. 6, which are sequentiallyobserved for flaws on a layer by layer basis. This technique may besuited when it is desirable to observe the entire surface of a specimenat a time.

Then, each time a flaw is detected, it is subjected to a minute scrutinyto determine its type and nature by varying the depth of observationalong a line directed toward the focal point of the flaw. Alternatively,the specimen 1 may be scanned for detection of flaws and each detectedflaw may be registered with data representing its position so that itmay be scrutinized by varying the depth of observation in a later stage.

A specimen shown in FIG. 5 was also examined for flaws and the type, thenumber and the size of each of the flaws were determined in threedifferent ways--by a method according to the invention and describedmore specifically in Example 1, a method employed in Comparative Example1 and a method used in Comparative Example 1. Table 4 show the result ofthese examinations.

EXAMPLE 2

A specimen prepared by slicing a polypropylene pellet to a thickness of0.2 mm was examined for flaws by means of the first embodiment of theinvention.

Two screen images (a) and (b) showing different flaws detected by thisexamination are illustrated in FIG. 11.

a₁ and b₁ indicate the respective flaws in the images (a) and (b).

(c) and (d) in FIG. 11 respectively and graphically show the levels ofbrightness of transmitted light along the dotted chain lines in theimages (a) and (b).

As only portions of the lines of graphs (c) and (d) of FIG. 11, onlyportions found in low brightness zones W (white) and high brightnesszones B (black) were electrically recognized by the embodiment, onlythose portions found in W or B zones were reproduced on the image screenof a microscope.

Consequently, images as (e) and (f) of FIG. 11 were obtained.

Thereafter, the types of the flaws of (a) and (b) were determined byvarying the depth of observation from shallow to deep along a linedirected toward the focal point of each flaw.

Table 5 shows the final result of the examination of Example 2 alongwith the result of an operation of determining flaws conducted on thesame specimen by an operator (Comparative Example 3) and that of anautomatic flaw detection obtained by using a known automatic method(Comparative Example 4).

As seen from Table 5, Example 2 produced a final result of examinationwhich is as accurate as that of Comparative Example 3, whereas theresult of Comparative Example 4 was by far less accurate and totallydifferent from those of both Example 2 and Comparative Example 3.

Therefore, it may be safely said again that a method of automaticallydetermining flaws of an object of examination according to the inventionis as highly reliable as a visual method involving an operator and canproduce results of examination with a remarkably high level of accuracywhich any conventional methods can never achieve.

EXAMPLE 3

Foreign objects in oil were trapped by means of a filter and thespecimen carrying the trapped objects was examined by the method of theinvention.

FIG. 12 shows a microscopic image where flaws of the specimen werecaught.

The flaws are indicated by a₁, b₁, c₁, d₁, e₁ and f₁ in FIG. 12.

The type and nature of each of the flaws were determined by varying thedepth of observation through the microscope along a line directed towardthe focal point of the flaw as in the case of Example 1.

Table 6 shows the final result of the examination of Example 3 alongwith the result of an operation of determining flaws conducted on thesame specimen by an operator (Comparative Example 5) and that of anautomatic flaw detection obtained by using a known automatic method(Comparative Example 6).

As seen from Table 6, Example 3 produced a final result of examinationwhich is as accurate as that of Comparative Example 5, whereas theresult of Comparative Example 6 was by far less accurate and totallydifferent from those of both Example 3 and Comparative Example 5.

Therefore, it may be safely said again that a method of automaticallydetermining flaws of an object of examination according to the inventionis as highly reliable as a visual method involving an operator and canproduce results of examination with a remarkably high level of accuracywhich any conventional methods can never achieve.

Now, another preferred embodiment of the invention will be described byreferring to FIG. 13.

Assume that a cable 13 having a cross section as shown in FIG. 15 isexamined for flaws but that the prepared specimen has a semisphericalirregularity formed, conversely to the irregularity 16 of FIG. 17(C), bya small portion of the transparent insulation layer 14 projecting intothe inner or outer semi-conductive layer 11 or 12 or, differentlystated, by a small depression in the black semi-conductive layer 11 or12.

For simplification, however, the flaw will be regarded as a black andprojecting semispherical irregularity 16 as shown in FIG. 17(C) in thefollowing description.

Rays of light from a light source L are transmitted through a specimen18 taken out from a cable 13 as shown in FIG. 15 through the interfaceof the inner or outer semi-conductive layer 11 or 12 and the insulationlayer 14 of the cable 13 and along stripes dividing the specimen todetect irregularities on the interface of the specimen 18.

After passing through the interface 14 of the semi-conductive layer 11or 12 and the insulation layer 14, the light is caused to pass throughan optical lens 22 for magnification of image and then converted intoelectric signals e.

An area of 500 μm² of a specimen will be examined by a single operationof microscopic examination through the optical lens 22 of thisembodiment as indicated by 18 of FIGS. 17(A) and 18. The specimen 18 isdivided into stripes a through i as shown in FIG. 18 and the brightnessof transmitted light for each of the strips a through i are convertedinto an electric signal by means of a photo-electric converter 23 toproduce signals e as indicated by 1a through 1i in FIG. 19.

The electric signals e of 1a through 1i are then converted intodifferentiated electric signals f indicated by 2a through 2i by adifferentiation circuit 24.

Of the differentiated electric signals f of 2a through 2i, portionsfound outside a threshold intensity level X are detected to produce somany irregularity signals (binarized signals) h for the interface 15 asindicated by 3a through 3i in FIG. 19.

For binarization, only portions of differentiated electric signalsnecessary for image processing are taken out, while the remainingunnecessary portions are discarded.

The binarized irregularity signals are then arranged on stripes thatcorrespond to those of the specimen as shown in FIG. 20.

A higher resolution can be achieved for a produced image of a specimenby dividing the specimen into a greater number of stripes. A highresolution image obtained by arranging binarized signals for thespecimen of FIG. 18 will show an irregularity which is very close to asemisphere as shown in FIG. 21 and therefore to the form of the originalirregularity.

Thereafter, the irregularity signals are further processed to determinethe width, the height and the surface area.

While the differentiated electric signal f shown in FIG. 13 has aportion g found without a threshold X of intensity, FIG. 14 shows adifferentiated electric signal f which is totally confined within thethreshold of intensity along with its original electric signal e and acorresponding binarized signal respectively indicated by (B), (A) and(C).

The threshold level X of intensity for differentiated electric signalsshould be so selected that the brightness of picture elements forirregularities and that of picture elements for surrounding areas(normal areas) show a remarkable contrast so that the difference in thebrightness among picture elements for irregularities may be hardlynoticeable.

An irregularity 16 can be easily detected when the interface 15 betweenthe semi-conductive layer 11 or 12 and the insulation layer 14 isconspicuous.

If the insulation layer 14 is poorly transparent, the transparency ofthe insulation layer 14 may be improved by heating the object ofexamination 17 to a temperature higher than the melting point of crystalof the material constituting the insulation layer 14.

The embodiment of FIG. 16 is suitably used for detection ofirregularities 16 in a specific specimen 18 of an object of examination17.

When an object of examination 17 has to be entirely examined fordetection of irregularities, the above describe technique of formingvirtual layers may well be used in a following way.

The object of examination 17 is divided into a number of virtual layershaving a given thickness and the multi-layered object 17 is subjected toa scanning operation that proceeds from the top layer on a layer bylayer basis by modifying the depth of observation for each layer so thatconsequently the entire object is examined for flaws.

An experiment was conducted by means of the embodiment of FIG. 13, whichwill be described below.

EXAMPLE 4

A specimen having a thickness of 0.5 mm (object of examination) wasprepared by slicing a 66 KV bridged polyethylene insulated power cable.

The object was then examined for flaws on the interface of the innersemi-conductive layer and the insulation layer by scanning with apredetermined depth of observation along the interface.

Irregularities on the interface as small as 1 μm were detected by thisscanning operation.

EXAMPLE 5

A specimen having a thickness of 2 mm was prepared from the cable ofExample 4 and was examined for flaws by scanning it while heating it toa temperature higher than its melting point (120° C.) in a manner sameas that of Example 4.

As a result of this operation, irregularities on the interface as smallas 1 μm were detected.

Since a method of automatically determining flaws of an object ofexamination by transmitting rays of light through the object to detectflaws on and in the object on a one by one basis according to theinvention comprises a step of adjusting the depth of observation inthree stages of making it agree with the focal length of a detectedflaw, go down deeper than the focal length and come up shallower thanthe focal length and converting the brightness of transmitted of lightinto a corresponding electric signal for each stage by photoelectricconversion means, a step of selecting portions of the generated signalthat are found outside a predetermined range of intensity as flawsignals and a step of comparing each of the flaw signals with a numberof binarized flaw patterns prepared from various flaws that have beendetected in advance, it can be suitably used to automatically andaccurately detect and determine black foreign objects, ambers and voidswhich are thee popular types of flaws can be automatically in objects ofexamination.

Moreover, since a method of automatically determining flaws of an objectof examination taken out of an inner or outer semi-conductive layer andan adjoining insulation layer of a cable by transmitting rays of lightthrough the object to detect flaws in the object according to theinvention comprises a step of converting the brightness of the lighttransmitted through the interface of the semi-conductive layer and theinsulation layer of said object of examination into a correspondingelectric signal by photoelectric conversion means and converting theobtained electric signal further into a corresponding differentiatedelectric signal and a step of selecting portions of the generated signalthat are found outside a predetermined range of intensity asirregularity signals, it can effectively eliminate noises due to scarson and/or an uneven thickness of the surface of the object ofexamination and therefore it can be advantageously used to detect anyblack irregularities as small as 1 μm existing on black interfaces toenhance the sensitivity and the accuracy of flaw detection.

Thus, the method of the present invention can significantly enhance thelevel of quality assurance of rubber or plastic insulated cables becauseof its high accuracy and sensitivity.

Moreover, the method of the present invention can remarkably reduce thetime, labor and cost required for detection and determination of flawssince flaws are automatically detected and determined for the type, sizeand number by using the method of the present invention. Additionally,the method of the present invention offers a wide scope of applicabilityfor flaw detection since it can be used for detection of flaws in anyobjects of examination so long as they provide a pattern of transmittedlight similar to that of an insulated cable.

The accuracy and reliability of flaw detection by using the method ofthe present invention can be further improved when the object ofexamination is divided into a number of virtual layers, which isobserved for flaw detection on a layer by layer basis.

Another technique of improving the accuracy and reliability of detectionof irregularities on interfaces of different layers by using the methodof the present invention is heating the object of examination to a giventemperature to enhance the transparency of the object of examination.

                  TABLE 1                                                         ______________________________________                                                  Over     Just       Under                                           ______________________________________                                        Foreign Object                                                                Amber       ⊚                                                                         ∘                                                                 unidentifiable                                         Void                   ⊚                                       ______________________________________                                    

                  TABLE 2                                                         ______________________________________                                                                          type of                                     k        l     m      n      o    foreign object                              ______________________________________                                        a.sub.1                                                                           none     B     B    B      none black foreign object                      b.sub.1                                                                           none     B     B    B      W    amber                                     b.sub.2                                                                           none     B     B, W B, W   none amber                                     c.sub.1                                                                           none     B     B    B      B    void                                      ______________________________________                                    

                  TABLE 3                                                         ______________________________________                                        foreign              Comparative Comparative                                  object   Example 1   Example 1   Example 2                                    ______________________________________                                        a.sub.1  black foreign                                                                             black foreign                                                                             black foreign                                         object      object      object                                       b.sub.1  amber       amber       black foreign                                                                 object                                       b.sub.2  amber       amber       amber                                        c.sub.1  void        void        black foreign                                                                 object                                       ______________________________________                                    

                  TABLE 4                                                         ______________________________________                                                             Comparative                                                                              Comparative                                   size μm                                                                             Example 1   Example 1  Example 2                                     ______________________________________                                        foreign                                                                       black object                                                                   1-10    12          11         360                                           11-20    2           2          9                                             21 and above                                                                           0           0          1                                             void                                                                           1-5     410         402        70                                             6-10    0           0          12                                            11 and above                                                                           0           0          2                                             amber                                                                          1-5     41          40         10                                             6-10    19          20         2                                             11-20    10          9          2                                             21 and above                                                                           1           1          0                                             ______________________________________                                    

                  TABLE 5                                                         ______________________________________                                                          Comparative   Comparative                                   flaw Example 2    Example 3     Example 4                                     ______________________________________                                        a.sub.1                                                                            opaque and black                                                                           opaque and black                                                                            opaque and black                                   foreign object                                                                             foreign object                                                                              foreign object                                b.sub.1                                                                            translucent  translucent a.black                                                                         opaque and black                                   a.black      foreign object                                                                              foreign object                                     foreign object                                                           ______________________________________                                    

                  TABLE 6                                                         ______________________________________                                                               Comparative                                                                              Comparative                                 foreign object                                                                             Example 3 Example 5  Example 6                                   ______________________________________                                        opaque foreign object                                                                      4         4          1                                           translucent  2         2          5                                           foreign object                                                                ______________________________________                                    

What is claimed is:
 1. A method of automatically determining flaws of anobject under examination by transmitting rays of light through theobject to detect flaws on and in the object on a one by one basis, themethod comprising the steps of:adjusting a depth of observation in threestages of identifying the focal length of a detected flaw on the basisof light intensity of transmitted light, deeper than the focal lengthand shallower than the focal length and converting the intensity oftransmitted light into a corresponding electric signal for each stage byphotoelectric conversion means, selecting portions of the generatedsignal that are found outside a predetermined range of intensity as flawsignals, and comparing each of the flaw signals with a number ofdigitized flaw patterns prepared from various flaws that have beendetected in advance.
 2. A method of automatically determining flaws ofan insulated cable having an inner or outer semi-conductive layer and anadjoining insulation layer comprising the steps of:transmitting lightthrough the cable, and converting the intensity of the light transmittedthrough an interface of the semi-conductive layer and the insulationlayer of said cable into a corresponding electric signal byphotoelectric conversion means, converting the obtained electric signalfurther into a corresponding differentiated electric signal, andselecting portions of the generated signal that are found outside apredetermined range of intensity as irregularity signals.
 3. A method ofautomatically determining flaws of an object according to claim 1,wherein the object of examination is divided into a number of layerswith respect to its thickness and each of the layers is examined forflaws.
 4. A method of automatically determining flaws of an objectaccording to claim 1, wherein, and further comprising the steps ofdetermining the type and nature of the flaw by varying the depth ofobservation relative to it for each flaw detected in the object.
 5. Amethod of automatically determining flaws of an object of examinationaccording to claim 1, and comprising the step of scanning an object fordetection of flaws and, upon completion of the scanning operation,varying the depth of observation along a line directed to the focalpoint of the flaw to scrutinize the flaw.
 6. A method of automaticallydetermining flaws of an insulated cable according to claim 2, whereinthe insulation layer of the cable is heated to a temperature higher thanthe melting point of a rubber plastic material containing crystals toimprove its transparency, and wherein light is transmitted through theinterface of said insulation layer and an adjacent semi-conductive layerwhile the insulation layer is transparent.